Qore Conversations
Tune in for engaging conversations about the latest technology, innovations, and trending issues in the automotive industry. QoreAi's podcast delivers expert insights, practical tips and problem-solving solutions. Stay informed and inspired with every episode.
Qore Conversations
How AI is Transforming Data Strategies for Modern Car Dealerships
Could the future of automotive dealerships hinge more on data than on the vehicles themselves? Join us for a riveting conversation with Todd Smith, the visionary founder and CEO of Core AI, as we explore this bold proposition. Todd brings his wealth of experience to the table, unpacking the transformative power of data and AI in the automotive industry. From outdated CRM systems to sophisticated AI-driven data strategies, Todd provides an enlightening perspective on how dealerships can unlock the full potential of their data.
Our discussion navigates the complex landscape of data lakes and Customer Data Platforms (CDPs), questioning their real value for dealerships. Todd candidly shares the often-overlooked pitfalls of adopting these trendy approaches without sufficient expertise, and the potential for AI to turn the tide by providing actionable insights instead of just collecting dust. We dive into the challenges and solutions for seamless data integration, offering practical advice on avoiding unnecessary vendor fees and enhancing data reliability.
Todd’s entrepreneurial journey, marked by both resistance and breakthroughs, provides a compelling narrative of innovation and adaptation. He emphasizes the crucial need for dealerships to embrace AI to stay competitive in a rapidly evolving market. As we wrap up, Todd shares a powerful message on the importance of data-driven strategies and the urgency for dealerships to transform their operations. Don’t miss this episode packed with valuable insights and practical strategies for modern dealerships looking to thrive in the digital age.
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Hello and welcome back to Core Conversations. I'm your host, sean Raines, and, of course, with me it's Todd Smith, founder and CEO of Core AI. For those of you that don't know by now, todd is clearly an expert in almost all things automotive data expert for sure. Definitely with a focus on customer engagement strategies for dealerships, todd. How are you doing engagement strategies for dealerships, todd?
Speaker 2:how are you doing? Listen, I'm doing great. You know been a very fun week. You know how it is being an entrepreneur you get your ups and downs. This week was good, so happy to be here today.
Speaker 1:Well, awesome For the audience listening and or watching. We're talking about building your dealerships, data strategy, and we're going to talk about some things that you don't hear about enough. You certainly don't hear more of a contrarian maybe perspective or challenging perspective, and so today we really want to help educate dealers, managers, data specialists, relative to the dealership, on how you're going to leverage data, modern data management systems. We're going to talk about some things that I think Todd would agree that are maybe myths surrounding some types of data integration. We're going to get into some things that I think Todd would agree that are maybe myths surrounding some types of data integration. We're going to get into a little bit of data lakes and talk a little CDP. So hopefully you guys are ready to learn about that, because there's a lot of discussion.
Speaker 1:This is one of those things where Todd and I we kind of laugh a little bit. There's a lot of people that talk about a lot of things. For what reason? Most dealers don't always ask Like why are you talking about this? Like what's the end game? I can tell you that this podcast, this episode for sure, is to really help you get educated and get comfortable about these things that you need to know why you're saying yes or no or maybe Very important. So the first place I want to start, todd, is really kind of an introduction, maybe. Just I know people know that data is important, but in your experience?
Speaker 2:how do you, how important do you think it's become for modern dealers? Well, I would have always said data is the most valuable asset of a dealership, I think, above their land, above their inventory, their building. I've always looked at data as the center of any business. I would say I'm going to amplify that up even more now because of AI, and AI only works with data. So I would say data has never been more important, ever in the history of time.
Speaker 2:And just thinking of data, I saw that AI is going to run out of data by like 2034. So think about that. That'll be. Ai will have consumed every known piece of data of humanity. Frightening to imagine what's going to happen. But yeah, I always said data was it. I think we would joke back in the day with first CRMs or DMSs, the importance of your data, and then now it's a thousand X more important. It's not 10 X more important. It is going to be the driver for your dealership's future success. And it's not just your customer data, it's your internal data. All the back and forth with employees, all the interactions with vendors, all of that data can be consumed by AI, analyzed, interpreted and ultimately turned into actionable insights.
Speaker 1:You know, in our industry we always end up having buzzwords, and it's now several years ago that people were talking about big data. Now, and you just had a recent piece of content that you put out there where you're talking about not just big data but even the small data, where you made this point that you could be preparing outbound campaigns to drive people into service on an oil change special, not realizing that you have a massive segment of your people that would have paid full price for that. But it's an example of things where it's like well, are we really just using data in ways that we spread the blanket out onto people? That a lot of people that don't even need the blanket? They're already warm enough. And that's just one micro example of multitudes around why data is so important. So I want to ask you a little bit on and let's get a follow up on that.
Speaker 2:I want to know what do we got Come?
Speaker 1:on. Let's talk a little CRMs. Great, Walk us through what you would consider benefits. I mean, clearly there's a top level of CRM benefit that everybody knows, but there's also limitations in the CRM systems that are currently being used by dealers, some of which have lasted for a long time. But it's a different world where you think about those limitations and you've got some interesting thoughts on it like you to share.
Speaker 2:Yeah. So if we think about CRMs in general, they were originally put in place to organize our customers and leads to manage relationships with, hence, customer relationship management software. It's always that amazing thing where, when you connect the dots backwards, you get to see the extrapolation and go maybe that wasn't the greatest idea. See the extrapolation and go, oh, maybe that wasn't the greatest idea as you speed it up right. We probably all have those instances in life when that kind of stuff happens and you know, we, I think with best intention.
Speaker 2:Crms were created to create an organized, managed journey of our leads and customers. Unfortunately, our customers do not behave like the organized journeys that you and I would probably spend weeks designing these follow-up campaigns for non-buyers or existing customer marketing through time to keep in touch with them over the three, five-year, seven-year cycle of their car. I feel like there's now such a disconnect between the traditional CRMs and look, they're all trying to adapt to some degree, but it's very hard to adapt the limited and older data structure to the modernality of what's available, with not only just the basic of customer data, which is what powers CRMs, but having true enhanced data, having real behavioral understanding of our customers, which really doesn't live in CRMs because they weren't built for that. I feel like everything is purpose-built, especially in our business, and I always look at CRMs as they were purpose-built between you and I to hold our staff accountable and to be a whipping post for productivity, right, I mean, that's really what the idea is, because every manager today is looking to CRM and saying, sean, like, hey, man, I'm looking here, there's 10 leads. What happened? What happened, man? What happened to those?
Speaker 2:And that sets up a bad experience, because it's like some of them could have been bad leads, bad phone number, and your salespeople are constantly in this defending themselves because and this all goes back to the key point, which is the systems allow bad data over the threshold into the system without being checked.
Speaker 2:And once that happens, then everything kind of breaks downstream. And I look at this world where, yeah, so if you let a bad lead in because it was gated, because on that website to get the e-price you had to put in a name and info, or to get the trade appraisal or whatever it was, I had to put in information and I didn't want to. Yet, because I'm still high funnel, I put in fake data that goes to CRM. Crm is trying to blow me up. Crm is sending emails to that address which then are getting caught up in the ISP as bad deliverable, which is now destroying that CRM vendor's ability to deliver mail to those people. Like you create such a problem downstream to me with bad data coming in and nobody pays attention to it, but it's definitely impacting the performance of every automotive CRM.
Speaker 1:Very interesting points and coming from somebody like you that has all these decades, well I will say I've been in this also for decades, so I go all the way back to the first decade man Come on CRM.
Speaker 2:That's true.
Speaker 1:I just, you know, no need to brag, but first CRM I ever remember was SalesPoint dedicated only to Ford dealers.
Speaker 1:Yeah, Microsoft, Microsoft so you know, I was working in downtown Seattle for that part of Reynolds in those days and I remember thinking some people didn't even call it CRM, they called it LMT, like a lead management tool, and I feel like the way we addicted dealers to leads and I say everyone that was slinging leads from Stone Age to Carpoint, all you know now into AutoTrader and everybody else that lead addiction for dealers I think oftentimes will cloud the ability in a modern setting like today to realize some of these things that you were just talking about limitations in some places where CRM isn't necessarily helpful at all In fact it's counterproductive and I think it is really important to think about the core benefits and then build on to what's really happening now, because what's happening now is monumental.
Speaker 1:It's so big we were talking about this in the green room, I guess, before we went live today it's so big that if you're actually behind, there is multiple scenarios that you could potentially never catch up and I think it's fascinating. I want to go into DMS with you. How do you think DMS tools are impacting operations at the dealership? What are some common challenges related to data, from accessibility and maybe even beyond that?
Speaker 2:Well, I think between both CRMs and DMS, they both struggle with data portability, being able to get data out of it and into other systems. You can do it. It's not very easy and it's also very costly and to me it's almost cost prohibitive in a lot of senses also very costly and to me it's almost cost prohibitive in a lot of senses. But you also look at the DMS again. You're dealing with like old monolithic architecture, right? So very tabled databases that don't offer the ability to take in all the available data that is possible today available data that is possible today. So a lot of limitations. I always still look with the current DMSs CRMs. I mean, there's still data in there and there's still value. But in the end this is why I think you're seeing these new products kind of spin up, trying to organize the data. But I feel like ultimately I saw a study recently it's like dealers don't even trust the data in their own systems. And I'm like, if you're not going to trust your own data and you're definitely not trusting a third party vendor's data, what are you going to trust? And it's interesting because then how do you call your CRM the source of truth? Or how do you call your DMS the source of truth if it's really not. And I look at that and I think it's super interesting that you know dealers are like it's got it all. Everything has to be in the CRM, because that's what they've heard. They've been kind of beat into their head that you have to have the source of truth. But what does that mean if you don't trust it? Today and I think we're entering a new era and AI is going to power a lot of that external data and intelligence, filling holes in the data that was kind of set up in the CRMs and DMSs, making data far more portable to use across applications that the dealer might want to use I see just a very different world opening up with data. And it's exciting to me because I think it's going to be the first time dealers are going to be able to deliver true personalization at scale.
Speaker 2:And I go back to a book. Do you remember that book? Peppers and Rogers. They wrote a book maybe it was like about 1994, called One-to-One Marketing. I mean, this is how old this concept is and it was done more for direct marketing being able to deliver a higher level of personalization.
Speaker 2:Honestly, I think we're right at the tipping point. We're going to see this come to fruition. It'll be a reality not only in dealerships, but every type of interaction can be much more personalized to you and, as you, I think, pointed out, sending that $9.99 oil change to all the people in your database. It's not only detrimental to your business financially, it's also detrimental to customer relationships, because the only people who should be getting that to me are lost leaders, people who haven't come in. They're not doing business with you yet, so you need the lure right the hook to drag them in. But your good customers you're now training them to look for those cheap incentives from you, so you're devaluing your company. You're now training them to look for those cheap incentives from you, so you're devaluing your company. You're devaluing your profitability by offering the same thing to every person. So the problem is, I don't think any dealers really had a system that could send mass personalization of delivering the one-to-one thing.
Speaker 2:That was, as I said, I think it was 1994. You can look up Peppers and Rogers. I think it's called one-to-one. But I mean, go old school. I don't know if it's even digitalized, unfortunately. You know it's one of those old books.
Speaker 1:There's still some old stuff out there. It's funny you mentioned something old because I've got a copy of Ogilvy on advertising, oh my god, dude, I I love uh, I I really like uh rory over an ogilvy at uk. That guy is like to me, like a genius of marketing, so yeah, yeah, he's like he's one of my favorites so well, I mean, that's a strong point where you say that dealers most of many of them don't even trust their own data.
Speaker 2:I didn't say it, it was the data that came out by one of the big companies. They surveyed thousands of stores. This was the input they got back. You know I would agree. You go into a lot of stores and are like I don't know, listen. And plus a lot of vendors I will say all vendors give curated views of the data back to their dealers. I mean there's one, won't mention names. They deliver, especially for groups, the data via a PowerPoint that they plug in the numbers.
Speaker 2:They won't even compile it in a pdf of screenshots from google analytics make it look nice but yeah, I know it's like you're not getting the raw data and listen, most dealers you don't. How's an actual dealer going to understand or shit like like, sift through the raw data to like, uh, create intelligence out of it? And this is where I think we're going with system of intelligence. We're heading in a direction that AI is going to be able to do things for dealers that you just couldn't have done. In this I'm not going to say analog world, analog world, but let's say more uh, excel spreadsheet filtered world, uh, with pivot tables, um, are going to look like dinosaurs, and I mean, they're already kind of look like dinosaurs with stuff we're seeing.
Speaker 2:But let's just say, within not even a year, like Because, think about this, I don't know, but you have retail experience too. How many hours are dealers wasting, or people in dealership compiling reports for end of month to somehow get a handle on what the hell happened operationally? And the problem is, you spent all this time to compile this data. You are only looking backwards in time. You have no understanding of what's going to happen. Going the other way.
Speaker 1:Yeah, that's a great thought, I think, a really, really important thing for people to be thinking about, because we have so many buzzwords. I mentioned big data, but people throw around disruption all the time. This is so disruptive, all these things, whether it's DMS disruption, CRM disruption but I don't know if you would agree with this, but I think right now, with what AI is doing, oh yeah, there is disruption now, but I almost think bullseye is on wrong targets for a lot of dealers, like they are still thinking 10 years ago, 15 years ago, and they don't maybe fully realize what is available to them now and what is not starting to grow. It is already on a trajectory that you can kind of see. You better get with it. Yeah, I don't like buzzwords, the disruptor thing oh listen, all these buzzwords look why do we use them.
Speaker 2:It's to capture attention, right, right, look at me, I got this new shiny toy. Come buy. The shiny toy Dealers love to buy shiny toys.
Speaker 2:It works in the ecosystem of it and look, there are some dealers that are on the hunt to solve problems. That's the real thing that I think and you cut through the buzzwords right but I think there's really good problems that can be solved with AI and data today that even 12 months ago would have been very difficult to solve, and that, to me, is the exciting thing, and I think I was able to say that with no buzzwords, because, well, ai is a buzzword. So let's just say, with modern technology, we're able to solve things that were almost unsolvable or took an enormous amount of time less than a year ago. See Buzzword less.
Speaker 1:Well, and you just gave me a perfect segue into a new buzzword, or?
Speaker 2:a new word and that would be data lake.
Speaker 1:Um, I am. I. I don't want to just, you know, give this pessimistic view of the. You know data lake as a buzzword, but I don't know that dealers really understand what's being talked about. When a lot of the buzzwords first hit the market and I would guess that you could take a 20 group and ask all 20 dealers represented to just if even one of you would like to stand up and explain what a data lake is they'd be like that's something that I hear all these pundit people talking about, but I'm not quite sure what it is or how it matters. So, sorry, a little bit of a buzzword Data lakes.
Speaker 1:I think are misunderstood in the dealership world, like if you would explain a little bit, like well, what really are they? How should dealerships? Can they benefit from them? How much is buzz versus substance?
Speaker 2:from them. How much is buzz versus, you know, substance? Okay, so a data lake. Let's just break it down into what it actually is. It's it's a data structure that enables structured data, meaning like coming out of, like you know, a table, like in a CRM or something all the way to unstructured data. So that's like a visitor to a website has an ID and click path, like just a bunch of disconnected data and it all can be thrown in this data lake.
Speaker 2:I will say what my CTO says data lakes are a great place where data goes to die, and I say that in the nicest way that because all you're doing is throwing all the data in one giant spot and then you got to have very sophisticated people to be able to go in and try to get value out of the lake. Right Of being able to pull the data, understanding where all the subset data is. It's not, they're not easy, and I think you remember that old saying like I've been to more BDC funerals than births, right, like I think we're gonna get, we're gonna be to more data lake like bombs than we'll see successes, especially in auto For giant companies that have tens of millions of dollars of resource data scientists top like machine learning engineers like that yes, they can use data at scale like that. They can take everything from the structured data to what I call like exhaust data. Right, car dealer? That's like it'd be like giving my 14 year old uh 911 gt3 in racetrack mode.
Speaker 2:He's probably going to hit something within five to ten seconds of putting the pedal to the metal and it's just overkill and it's a trendy term that I've seen some groups try. I've also seen some groups already fail uh to be able to make a data lake truly viable. They'll say they're getting pieces out of it but they're just hanging on to the fact that they don't have the in-house true data understanding to really make value of it. But think about it in concept it makes sense hey, get all our data going to one spot and then we'll figure out what to do with it and how to use it down the road. So it's kind of like a stocked pond, but you don't have any fishing gear, fish in there, but you have no idea how to get them out.
Speaker 2:So most guys, you'll end up just draining the lake right, so that's kind of the problem.
Speaker 1:So don't let your data drown in its own lake.
Speaker 2:Yeah, and it happens all the time. Listen, our CTO said it. Perfect, he goes, data goes to die in data lakes. I was like that's such an interesting concept because you would think like, oh, that's like the best place for it, the best place for it, but for giant companies, sure, yeah, who are resource intent, that like have the IT professionals, scientists, all that stuff, sure?
Speaker 1:How many data scientists do?
Speaker 2:you know, work for car dealers. Yeah, right, right. Have you ever talked to one? Yeah, Like in a and I'm not saying like the publics, the publics have a few inside spaces, yeah. A car dealer. Do any data scientists work for even groups like smaller groups? If you have under 50 stores, most likely not, so in the end I feel like it's a great in theory, but they're also just hard to just transform the data into value.
Speaker 1:Yeah, yeah the data into value. So, yeah, yeah. So I think that's an important point for people, because when somebody starts to come in and talk about this new thing that you are like what's a data lake and does that matter? And oh, is that all my data in the lake? And then, well, what can I do with all of this? Do I just swim with my data in the lake, or, yeah, you kind of.
Speaker 2:I mean, think about this. It's just a giant storage bin. I mean, you still have to write all the processing on top of it.
Speaker 2:it's not as I said, that's not for the faint of heart, I mean yeah and look, I believe dealers prefer, like the one, one throat, to choke right, like and you're not building a data lake and going and choking that die, like you need other guys to go choke. And then it gets too complicated and then marketing guys can't. They're like where's the data? What do I use? Go choke, and then it gets too complicated and then marketing guys can't. They're like where's the data? What do I use? Nobody understands. And then you have very technical people who don't understand the car business and then you have car people who don't understand the technical side. And then you have this, this miscommunication in constant flux.
Speaker 1:So yeah our business.
Speaker 2:I'm going to do the good Caesar or what was this was bad, right, and we'll just say this is bad for the tv version.
Speaker 1:So I think it's really good that you make the distinction, though, that you know, if you were a mass, if your company outs even outside of automotive, but if your company is a tech company, a huge s SaaS company and all.
Speaker 1:We take things that are conceptually perhaps viable from other places and then we think how do we now put these things square pegs and round holes, oftentimes into the retail dealership environment From a marketing perspective? I tell people all the time, if you you're trying to, as a business to business marketing, uh, action do things that are the same as the direct consumer style marketing, right, something that somebody's like every time I buy shoes, I always buy adidas. They already love your brand, like that's a. Just the stuff you do. There is very, very different, but you will take that example and see that people want to do the exact same things in a B2B example. Then they wonder why it doesn't work, and I think that could be not the best example, but there are a lot of things that get pushed down to the dealer level that they think, oh, what is the value of this when really there may not be any at all for you, because it's, you know, for those same reasons that you're.
Speaker 2:Yeah, I just don't see it as the best solution. As I said, maybe giant publics that have hundreds and hundreds of stores, so it's just a tremendous amount. They have resources to like. You could create a whole big department that just deals with data, right, yeah, but you have three stores, five stores, 10 stores. There's no way you're gonna spend that money to make it valuable yeah, you're.
Speaker 2:You're a dealership or a group, or even a public, but you're not oracle right yeah, like I mean, think about, even like a dealer, even a big group is tiny in comparison to like the, like these giant oracle bass. Not even close the amount of data that's moving through some of these giant global organizations, but I'm going to say some of the big dealer groups. There is a lot of data and I don't even think they've truly figured out how to monetize it and turn it into value, because to me it's like you have to get it into something that's super usable but then be able to mine it in a way that's highly effective.
Speaker 1:so yeah, yeah. Well, that kind of leads me into the next area I want to talk to you about, which is, uh, another acronym, okay, cdps customer data platforms. And I will say this as I get ready to ask you a little question on your thoughts here. I know there's an expense that in the beginning dealers don't realize Like, oh, my goodness, that's a little spendy, so is the juice worth the squeeze? But there are people that have been down this path for quite some time and, like you just said, I'm not going to mention any names, but I know there are some that have deployed they're market viable, they're out there.
Speaker 1:And what they were hoping they were going to get from said CDP personalizing all of this information they really thought that they were going to improve. The second, third, the multiple time visits, because it's enhancing this personalized and making the customer experience that much better. And that wasn't what they found. Of course, I don't think they want to disclose that type of stuff out into the public. Really, the wins that they were looking for, the goals that people were looking for. I'm not saying that there's no value in it at all, but I do think it's really good that it's being talked about on both sides of, like you know, is there value. So I guess this would be helpful. How does CDPs differ from your traditional CRM, maybe? What potential value do you think or do they offer? Is it fool's gold or is there some value in it? It's certainly another buzz acronym, or is there?
Speaker 2:some value in it. It's certainly another buzz acronym. I'm going to say value that again. Dealers, just like the data lake. It's a little complex. Cdp again, still premise to try to get all the data in one place. Okay, organize the dealer data, clean it up, I have a nucleus for it. A dealer data clean it up, I have a nucleus for it.
Speaker 2:Now, problem I've seen with CDPs are a data business, but yet in automotive they're a marketing business. So I feel like you can't be a jack of all trades. So and I see that every, virtually every CDP in automotive is and it's funny, I made this using Dolly, I put a wolf in sheep's clothing in the dealership. My son and I were dying laughing, creating this because I felt like it's a marketing company who has like well, we have a CDP like in the center of it, and I was like well, you're either a data company or you're a marketing company. And I think auto is a weird thing where we see those two things merge together very frequently, and I think it has to do with dealers want one throat to choke, so they say, ok, I want my data there. Now you're going to do the marketing, because I'm not going to do the marketing and I think so far what I've seen, that limited value and usefulness from what's available currently in the CDP space. Now I think it has to do not. I think it's crap in, crap out. So limited data coming from the DMS CRM into this cleaned up, organized.
Speaker 2:You still don't really understand the customer or the depth of the customer, behavioral attributes, all the what I consider intelligence around it. You just kind of have the customer behavioral attributes, all the what I consider intelligence around it. You just kind of have the customer file and now you're trying to create triggers and some maybe I've seen triggers maybe off of like hey, they visited the website, but you don't really understand the customer behind that website visit, right, you see a behavioral attribute like a action, but you don't really understand much around the customer. Because I think the more you understood the customer you could behaviorally influence them. I think you're still kind of playing a hit and miss game. So to me a CDP is just a more organized database, a more modernized database that can take data from DMS, crm, even website and other sources, kind of put it into one spot.
Speaker 2:But then I feel dealers are like, okay, now send the marketing out. So now you have people that, okay, how are you going to deal with that data business, which is incredibly complicated, right? And now all of a sudden, you're going to spin up a whole other side. That's going to be experts at targeting marketing, content creation, you know graphic designs and that's that's auto. And it's weird because if we go outside of auto it's church and state. You have giant CDPs that are data companies, and then you have fulfillment companies and they talk and they connect the data across the stream. But in auto you're seeing them kind of lumped into kind of a haphazard thing and look again, buzzword wise, it's a shiny thing, something else to sell the dealer.
Speaker 2:It's kind of awkward to say like, okay, I can't get all this out of my CRM and my DMS. They suck for whatever reason to do marketing. So now I'm going to have the CDP, now I'm going to spend a ton of money sending all the stuff out there. But I always equate this back to me. The Achilles of this, honestly, sean, is that back to me. The Achilles of this, honestly, sean, is that okay, you hired a CDP Attaboy, you have all your data in one spot. Now, good, your marketing is going out. You're like I don't like the CDP. The marketing sucks. I'm not getting my results, so you fire them, you're right back to the same spot and you go backwards. Problem. So I just don't ultimately see that as the answer to leverage AI is a data business Like you have to have data to leverage AI, and dealers will never have the necessary data to effectively leverage AI in their business. Sorry, I crossed a few things there.
Speaker 1:Yeah, no, it's really good, and I always look for sometimes buried leads or points of value. You mentioned it a couple of times there in that answer. We probably have done the retail side of automotive a disservice by. I mean, we've kind of taught dealers to want that one throat to choke and that separation of church and state that's found outside of the automotive vertical and there are a lot of reasons and I'm not going to actually get into it on the episode because I think people would not like the criticism of how some of the way that programs get put together that make it really appealing for the dealer to have everything in one place and I can just go here, but to their own detriment oftentimes, because it doesn't mean that you're getting the best and it doesn't mean that actually separation is your friend. It really is in a lot of cases so.
Speaker 1:But it does take me into something just a little bit of another buzz-ish word, but relative to data. There's perhaps the myth of what's called bi-directional data and value. There's a lot of people that talk about this bidirectional data integration and again, and the reason why I love having these episodes and hosting your podcast for you is because you have so much information that I think dealers need to know about when it comes to these things that arm them with. Oh, here's some truth, here's some real stuff. So would you explain your thoughts here on why you think these integrations maybe are not as valuable as maybe dealers or people that want dealers to adopt this thing? On bi-directional data value.
Speaker 2:Yeah, okay. So let's go back that auto is unique and I'm going to go all the way back to the thinking that auto is unique in they charge to move data between systems. Business In auto. Certain companies are protecting the data as if it's theirs and then charging to relocate the data into another tool and my thinking and I am not a big. I devalue bi-directional data because I can see the schematic of the API of what data moves. How valuable is that data that's moving and how much does it having to pay to move their own data into a tool they want to use? Own people created by inputting it, or the customer created the data through a lead that now the vendor is going to charge to move data that they didn't create and to connect it to another tool and then they charge that tool. The vendor charges that tool also to receive that data. So I think a couple of these vendors were like, okay, I can't squeeze any more money out of the dealer, I'm going to go squeeze the vendor. The vendor can charge the dealer, but I didn't charge the dealer, the dealer, but I didn't charge the dealer yet I have made. It was a way to make far more money on dealers by leveraging the vendors and tools trying to connect, and it has stymied innovation in our space. It has limited true innovation in our space by doing this, because things become cost ineffective and tools can't work some without data, and it has left us with legacy tools that are so outdated to modern business practice. And here we are today. So I view it.
Speaker 2:I wrote an article about this recently, so I'm still hyped about it. I said for a dealer, it's like ordering a pizza pie, paying for it twice and then getting it delivered and they told you what toppings were going to be on it. You didn't even get it and you're like what happened? And they'll deliver it when they want and you're like or they won't deliver it, they change something and it breaks.
Speaker 2:So I think dealers should wake up to the simple fact that they're being far overcharged for data that they're not controlling. So if I went back to my retail roots, the first thing I'd be thinking is no, I want to get complete, I need to arm my arms around all my data. I got to control it and then I want to control the distribution of my data and I'm not paying crap to do that. And yeah, and I feel like auto and APIs. It's very pay to play unfairly and it only hurts the dealer and it also hurts small companies who may have truly innovative products but will never get scale because these large companies will ensure that they don't get scale.
Speaker 1:Yeah, it is very interesting how it works in automotive when people start paying attention to it. And you actually answered into the next thing I was going to ask you about, which is really a lot of. There's a lot that end up being hidden, especially around the maintenance side, like the maintaining of some of these data integrations. It's not just, hey, we're going to hit you with the toll for the data coming in or the data going out, or both, but it's also a lot of them will have this oh, there's a little. Oh yeah, there's a tiny thing, and if it's something delivered by a vendor, that you have multiple line items on your invoice from them.
Speaker 1:I'm again not going to name names. Yeah, you won't even know.
Speaker 2:You won't even know that they're getting another little extra tax on you for something that is not helping you and probably super unnecessary, like you're dying by a thousand cuts of data movement and you're getting truly no operational benefit for the amount of data moving in most cases between systems. I'll give you I will not mention the name of the company we went to do like for us, even like we went to do an integration I mean, we're a vendor too. So we went to them and said, hey, we already have the form on our side, we just want to pass the data to you. So they said, well, you have to go through our whole API certification process. And we're like, okay, we charge you $2,500 a month while you go through that process. And we're like okay. And I was like, well, who controls that they do. So they could say, oh, push us this this week, push us that that didn't work, so they can control that cadence of integration. And then they said they want $125 or $150 per rooftop fee to integrate.
Speaker 2:And I, honestly, I was like no. And at the end I was like definitely no, because I don't know. I see someone like Anthropic or someone using like autonomous agents that will go fetch the data out of these systems for nothing and destroy the entire API marketplace at some point because of AI. But I saw more of a. I had to finally put my foot down. I was like we're never going to pay to integrate data and I'm for the dealer. And I went back to the dealer group I was like I don't want to pay for this and I was like I don't think you should pay for it, so let's figure out something else or just use them less. We can push it to another service that didn't charge us. So you know, I feel like dealers need to look at this side of their business very seriously, seriously. But the biggest part of this to me is dealers need to become their own source of data truth and pick a data partner that is going to live with you forever, like you're never leaving them over.
Speaker 2:Data storage management enhancement right, you'll leave your marketing vendors. You'll leave all them, because things creative juices dry up in agencies and you want to switch. You want a new face. You know you want these things, but your data and managing your data can be the next 10 years, as long as they're an innovative company. They're using AI to power your data. They're enhancing your data. They're keeping it evergreen, keeping it constantly updating, because CRMs don't do that, dmss don't do that and we know.
Speaker 2:Just I mean on a simple thing email addresses alone decay at a rate of 2.5% per month. So, mathematically, 30% of your emails in your CRM right now are bust right now. So if I take that data and you tried to send a mass mailer which they all do, right, mass text out or mass email out, if 10% of your database bounces, the ISPs will restrict deliverability to about 40%. So if you had a 100,000 person list, you bounced it, less than 40,000 are going to get delivered. But do it on a different math. Like you have 10,000. Like you're not getting near the reach if you have bad data, and so true. And now they want to charge you to move bad data to another system. No, look, I would pay to move data If you.
Speaker 2:You went in there, you know, you worked it out. You made a big buff, you got it healthy. You, you cleaned it up, you enriched it. You, big and buff, you got it healthy, you cleaned it up, you enriched it. You, as your business, added value to it. Okay, I can see that. But if you're just taking the crap and now moving it to another crap located, there's no value there.
Speaker 1:Yeah, it's almost like a hostage and ransom situation. We take your data, we hold it hostage and then we charge you these ransoms for us to not ever come back and say, oh, by the way, for the $2,500 a month we charge the vendor or then, ultimately, all the things that they're hitting the dealer for. Here's all the added up fees, but here's the value you get. This is how much more efficient it made your business operationally. Here's the percentage of profitability that got added to the bottom line in the last quarter. Blah, blah, blah. There's none of that. It's just nope, just pay the ransom. We're using your data as the hostage for this scenario. What?
Speaker 1:was his name.
Speaker 2:Asbury right Sued CDK and I think they just won because again, they just wouldn't give up the data because Asbury's moving to Techium. So you think about that. I could imagine a vendor. I could imagine going to MailChimp and MailChimp suing that says we're not giving you your data back Right, that says we're not giving you your data back Right. Like it's almost preposterous in my mind. Yes, and I have zero idea of, like the legal ramification, how that ever happened that they let these companies, any of these companies be the owner or co-owner of their data. Now I get that some of these companies can offer a level of protection around the data to secure it in some cases. Some cases obviously not, but you know every company's at risk of security, so I won't even blame them for that. But you know, at the end of the day, you know.
Speaker 2:I feel dealers still need a partner, because they're not going to do this by themselves, but they need a partner that behaves more like an AWS for them than a partner who's just sending out marketing messages for them, who's pretending to be a data company by the way, the AWS is a great example actually.
Speaker 2:That's kind of how I look at it. Right, you want a partner because you're not going to do that, but you want a partner who's going to be your data partner for the next 20 years. Right, and they're going to help you. They're going to protect your data, secure your data. They're going to help you empower your data to be useful. They can work to obviously run, enhance your data, provide intelligence around your data. They can work to obviously run enhance your data, provide intelligence around your data.
Speaker 2:But, you know they're not doing the shiny content creation. You know you couldn't call up AWS and say hey, do you build me a great marketing program?
Speaker 1:you know, with my 10,000 people in my database, you know they'll say go over there, talk to that other guy, right, yeah yeah, the separation of church and state. A couple minutes ago, you mentioned something that I think that it'll be good for the audience to hear you explain, and that is evergreen data. I think some people are like, oh, I've maybe heard of that term, or evergreen, what does that really mean? So tell the audience what is evergreen data, um, and is it important for dealers?
Speaker 2:yeah. So think of evergreen as, like your pine tree, right needles don't fall off, right stays alive year-round. It's cool, right. So same evergreen data is just that your data forest stays alive. It's staying like updating, it's being enriched, it's changing, because data is not a stagnant thing.
Speaker 2:I think a lot of times we've looked at data as like it's just names in a table. But when you start connecting data and enriching it, it comes alive, it changes. People come to visit the website that appends to the data. Things are happening around that customer in their life they get married, they have a baby, they crashed a car, they're now back in the hunt, they just bought a house. There's so many variables that surround a name and a table.
Speaker 2:Today and now, with how technology works, you can harness all that, and that, to me, creates an evergreen data structure that your data is now alive, it's breathing and it's staying updated, and with the most accurate data profile around that customer and the most behavioral intelligence attached to that customer. I think that is how we have to think about data to build this living, breathing data engine that you can then leverage. So, to me, I have never seen an evergreen thing in automotive. Now that you mentioned this. Um, everything in auto has been static to this point. But if you look outside our business and look, I think me, myself and martin rct we we spent our development. We spent a ton of time not looking at auto because the innovation's not happening here.
Speaker 2:I don't know what you mean, innovation is happening all over the place, but it's in other industries and just not here. So our goal has been to learn and what can we bring back and what can we apply? But, even thinking, when we originally thought about data, the key to this was well, this has to be dynamically changing data, because you can't just leave it and expect it to be at the same level of performance because of just decay. And that's why I mean, someone told me like 40% of the data in a DMS usually is bad. I don't know if that's an accurate stat.
Speaker 2:It would not surprise me at all, and I look at that as just those systems aren't built to be evergreen. They're old systems, I mean, and there's nothing wrong with that. They have led this industry for many years. They were built to serve a purpose. The problem is we're now moving in a world of data that's transcending their purpose. Like the kids are growing up, there's new things out there we don't need. Like you know, my bell is turning off your rotary phone. You're going to need to get a cell phone, folks yeah, right, yeah, yeah, that's a good, good example.
Speaker 1:Yeah, the evergreen concept, you're right, I don't. I don't really see a lot of that. I maybe on the marketing side, where somebody says, hey, let's evergreen some of your content, which is also data. Um, it, it really isn't some data. Maybe it has a short life cycle, right, its lifespan is like it served its purpose and it's moved on. But within the dealer world and within the automotive world, there's a whole bunch of that that should be evergreen, meaning it has this forever lifespan. It has a purpose that is much more than just one and done.
Speaker 2:Yeah, because all't think signals, think about it. They're attaching to you and with ai, all those signals are getting me closer to understanding you yeah, I mean not, you're gonna matter to your end user, yeah right, same as same as amazon.
Speaker 2:Right, there are cons. Every time you're buying what you're buying, when you're buying it uh, things you're looking at things, you're searching for what, you're reading reviews on all the everything you're doing is being collected and put against you as a human. And then the algos start understanding that and listen, they're damn good at serving you up stuff today.
Speaker 1:Yeah.
Speaker 2:Right.
Speaker 2:It's like Todd, you need toothpaste. I was like, do I? And then the last squirt goes out and I was like, yep, needed toothpaste. It was right today, yeah, and then you're like, okay, but I think a lot of this is and it's so crazy because I now just use Amazon as that example Like I went toward an Amazon distribution center, right, and I was so confused A there was robots, which I thought was awesome to see robots go and pick stuff and they had this other robot that went into the truck and pulled boxes off, it used the suction thing and put on a conveyor, which is cool because Florida gets really hot, so these guys in these trucks were overheating and like passing out.
Speaker 2:So now they have this robot that does it, which I thought was super cool. But my point was you would see these bins and a bunch of random crap in the bin. Bunch of random crap in the bin box of cereal, uh, tennis balls, uh, a bathing suit, uh, granola, excuse me, uh, you would see these random items in a bin, but they're co-located because they know people order these things together I was like think of the algorithm that's predicting that stuff.
Speaker 2:I'm like, and it's less walking less, so the pickers can do more within arm street. I'm like, dude, this is such a science, it's so awesome, but I know, and. But then I look at our business and we're like you know, you're getting the same mailer, uh, to tell you to come in and service a car that you never drive. Or I'm still getting mailers from a mercedes store, uh, and I haven't had that uh s 500 for like freaking five years. So so I look at you know we are still archaic cavemen when it comes to using data For our benefit. As a dealer. We are still. 99% of dealers are cavemen.
Speaker 2:Yeah, I'll say there's one there's a couple that are they're interested in this. I haven't seen anyone that just owns this space yet, but I think there's always those bleeding edge guys who go, oh man, we got to leverage it. But I think today we have to remove. A lot of times we still are looking at data in a constraint thinking fashion.
Speaker 1:I think that's right. Not everybody's ready for a robot, although, man, I would have liked him. Back in the 90s my entry into the car business was in parts warehousing and I would literally go in on weekends, get on the forklift myself and move all of the you know 90 to 93 Honda Accord oil filters as close to our packing tables for our drivers to take out to dealers just to improve operational efficiency. And so you share examples of things like touring Amazon and all of this. It's. I don't think I'm the only one.
Speaker 1:I know that you and I talk about these things all the time. I think everyone. Once they have this type of practical, educational insights that you talk about all the time, they can use their own life, their own stories, their own examples of like, oh, I get it. And then you start to see these new opportunities of things that just weren't even. There was no innovation here because these things didn't exist. And now we're in this new era. I few last things I want to ask in this episode. I want to make sure I make a little time for this.
Speaker 2:Um, so ai hot topic sure, welcome to your buzzwords, sean. Good job I know this is the buzzword episode, it's not'll just call it the buzziest episode yet for conversations, right?
Speaker 1:Introduction to buzzwords. Automotive 101 buzzwords there we go.
Speaker 1:But you and I I mean, obviously the foundation of Core AI has a whole bunch of artificial intelligence, all the things that you're thinking about. Before we went live on the episode today, you were showing some of your emerging stuff to me and I was like, oh my goodness. So AI and dealership data management is a topic that a lot of people are talking about. What are your thoughts on how you see AI transforming data management in the dealership space? Maybe even a potential application or two, if anything comes to mind?
Speaker 2:Yeah, absolutely. First thing, I think of AI, which is in our name, right for a reason, because we built around an AI nucleus. I mean, the center of core is that we wanted an AI neural engine we call it Q that could just learn and understand data in a way that we could just add value. And it could be different things like we do it around driver's license identity, right, Using AI. There. We've done it around understanding conversations through messaging whether it's internal messaging or external to consumers and wrapping all that conversation and learning from it, right, and giving insight and hey, maybe we can do this or this is what the customer might need. Next, there's a whole future around that.
Speaker 2:But when I look at data for the dealership's data, when you take the dealership's data, you clean it, enhance it, household it, normalize it, you get it in the right spot and then you put all the behavioral attributes around it. Ai is built for that. You know, with like what's called random forest or like pattern matching, to be able to see things in the data that people we just don't see. You know, like being able to look inside your data, knowing who's in market, matching that to inventory. To me that's low-hanging fruit. It'd be super difficult. The average dealer is not doing that. But dealers pull up their overage unit and go crap, what do I do? Let's lower the price or send it to the auction. But I'm like, well, what do I do? Let's lower the price, right, or send it to the auction. But I'm like, well, what happens if you have customers who are in market right now that are looking for those things? And this is that problem.
Speaker 2:I always run in with dealers. There's two types of dealers I talk to. I'll talk to the one dealer and I'll go how many people in your database right now are in market? And I'll get half that goes, I have no idea. Good, legitimate answer. The other half have some, like you know, suave to them. They'll go one to three percent of my customers are in market and I'm like you read that in a book, I love it, and I always say which one to 3%. And they're like eh, got me there, todd, I don't know.
Speaker 2:And I was like well, with data today we can see that, right, we can really ID and not using model data, using actual behavioral data, look and go. Okay, this customer's doing these things right now, that their propensity to buy is within a week, a month, like days, like you can really granularly understand your customers and then you can understand what can they afford, most likely what car they're going to buy because of the cohort they live in, type of personality they are. All of those things to me come alive very fast when you leverage AI across data. It can very quickly make those connections and highlight them out. And I see, like you know, to me easy to type in okay, show me all my overage cars, match them to inventory or match them to customers who are in market. See if I have any connects. Okay, now send that to the BDC or send it to an email campaign or I don't know. Call them. Hey, let's be crazy, let's call some people today. You know, I mean, you could do that, you could do. Okay, how many people leads didn't buy from me? What did they buy when?
Speaker 2:Yeah, you know, I think once you have all the data in, like AI is really good at and I think this is the learning lesson, like we're still learning where what can I ask it? And then we started to realize crap, we could really ask it all kinds of things. As long as the base data is there, we can correlate things that before were almost impossible to correlate. We would have to take like a okay, run a report out of the auto, get my overage things, now go to my marketing company or figure out somewhere how to get customers and and then now try to match these things and like it was a very clunky, archaic way to do things. And now, with natural language and these powers of LLMs, like we built like what's called like between Q, our system, and like a power of a big LLM like Mistral or any of them you know, we have like a rag, so it's like a retrieval augmentation process, so we never let the data out the dealer's data never leaves, but we can leverage the power of those systems on top of the dealer's data.
Speaker 2:And to me that's just a new way to look at things. And frankly, I'm tired of dashboards and reports that are only telling me what happened. It's like you know it'd be. Like all of a sudden stand on Titanic and dude comes up. Dude, you hit an iceberg and you're like crap. Like it's too late, right, like dude, when you bunked your month, it's too late, there's no fixing it. Like. Then you're like oh my God, now I'm double dipping and trying to figure out how to make next month like start off with a bang and like you're behind the eight ball, and I think this is the world where AI not only understands things based on, it can start to look out and now start to predict what's going to happen.
Speaker 2:Think of LLMs. What is an LLM? At the most basic understanding, it predicts the next word in a series of words. That's what it is, and it's gotten better and better. So don't you think? Using that same architectural thinking, once it looks at your data, it will start predicting that what's going to happen next, and I do think there's balance in this. Honestly, sharon, we predict it now. I start taking actions to it. So it's going to increase the probability of those things happening, which is good, especially if it's driving where we want it to go. But I look at AI as not only this is going to be the generational shift for how we leverage data and AI is going to be the driver for that, and it's not just to me.
Speaker 2:Sales and marketing data, and it seems like we talked about CDPs before. Everybody's just focused on that and it's important. Sell more cars, sell more cars, I got it. But all this data that your dealership is kicking off internal conversations, right, running payments for people that don't buy All of this data. If you can extract it, ai rips through data at an enormous pace, right?
Speaker 2:I think I said like we're going to run out of data, as predicted by all data, all of humanity's data. By 2034 that AI will have ripped through it all, which is almost frightening to think of. But think it's not going to like quantify your data at a dealership. Of course it is At super fast scale all your service data time to repair shop load. Once you can gather your arms around that data and get it into a system that can actually process it, which is not a DMS, not a CRM, not most likely a CDP, when you really put it into what I call like a system of intelligence, bar the door, katie, it's gone. Dealers this will be the difference between dealers that have the highest level of efficiency will also be by far the most profitable.
Speaker 1:Yeah, I think you're 100% right about that.
Speaker 2:Yeah, I mean it's, it's. It's an amazing time that and as I said from the beginning, like if I could think of a dealer, data is your absolute most valuable asset or it's. It's a rock sitting there that's doing nothing, because I could look at a rock in the ground and it's a diamond, but it's in the ground. It does nothing unless I get it out, polish it right, cut it, craft it, and now it's worth hundreds of millions of dollars.
Speaker 1:Yeah Right, great analogy.
Speaker 2:And to me, this is what we're at this fulcrum point right now, and I believe the dealers that start to think and leverage AI are going to be so far ahead of their peers, their competitors, everyone. And the thing with AI there's no, you can't catch up, Meaning like, once your horse leaves the barn, your competitor's horse leaves the barn, you're still going at an exponential rate forward. Even if they go at an exponential rate forward, they're not going to surpass you. So to me, this is definitely a time in history where you getting in and starting to train and leverage the data, because it's very unique to you, the insights are unique to your organization.
Speaker 2:You can't globally train all dealerships with AI. They're all behaved differently and one model will not work for everyone. Every store will be individualized type of people who work there, type of cars they sell, type of customers in the local PMA, all those things, banks they deal with all of that information is unique like a fingerprint, and dealers need to get a handle on that and get that in their mindset. That it's like today is the day to start, Because tomorrow, if your competitor started today and you start tomorrow, he already got a day on you and a day might not seem like a lot in this world, but a day in AI processing tech is I mean, you might as well call it 100 years.
Speaker 1:I can't begin to overemphasize how significant that point of value is that you're dropping there. It's really, really important and it segues into. I just have a couple of things I want to ask before we land this plane. It segues into that. Our industry still has resistance and I know there are a lot of people that think well, the auto industry is, you know, we adopt things pretty quickly, we're always on the cutting edge, we're super innovative. I don't know if I've ever believed that, but the auto industry, in all honesty, in comparison to other verticals, has been kind of slow to adopt AI. You see it a lot in people doing marketing stuff. Hey, chat GPT, you know, go write all of our social posts or things like that. You have people using it in the basics of marketing.
Speaker 1:But I'm curious to know your thoughts on why you think maybe some of the reasons behind resistance and if you even have thoughts or things that you might share to dealers in this listening audience on how maybe they could overcome it if they're feeling still that resistance. Because what you just said, I think that's really important for the dealer who might think, ah, we don't need this, it's not important, I'm small, my market doesn't matter, none of those things region, all those things are not. They will fixate on something that will keep them in the barn when someone else's horse started running the race and, like you said, one day, that's one day. You'll never get back two days to a week a month, and that can become really consequential for people until it's too late to realize what did we do? So anyway, thoughts on your, on the resistance here, maybe how dealerships could overcome that and embrace it so they don't end up having somebody that's lapping them.
Speaker 2:Yeah, okay. So the first thing I would say to this is what we have seen in auto, because of the limited amount of data, the AI it's not. It hasn't been smart and we've only seen it in like chatbots and they haven't had a wealth of data to train these bots on. So think of AI works with data. The more data it's like a fire the more fuel you put in, the brighter it burns. And what we've seen to date in many instances is like a smolder because of the limitations of data moving out of systems into a centralized system that then AI could power and understand. So that's the first part of that. I look at. This is why I'm that proponent that says free your data. Look at you know, this is why I'm that proponent that says free your data, free your data, because I realized that once a dealer frees his data into a point where he owns and controls it, he can truly now unleash the power of AI. But we just haven't really seen that quite yet. But we just haven't really seen that quite yet. So we've seen the little things, the chatbot not really work or it's someone just threw chat GPT on a website and it's freaking untrained and it goes wild and I'll sell you a car for a buck. Well, of course, if you put something out there with no bumpers to it because what we end up doing a lot of times when you're thinking about you write prompts, right, and then you train it You're like the guy keeping like the ball bowling down. So you're like the gutterless dude right, don't let it fall off, and I'll sell you a car for a dollar. We'll even deliver it to your house, right? Um, so I think a lot of this is ultimately, uh, having the intelligence or the partner of intelligence that's spending the time training the models off more and more data. Like you, honestly, you can't put too much data into these things. Hence, why, like, even for us, we're like okay, we have all the dealer data, but that's not enough. We need way more data. So we partner with huge companies like Equifax and all, because we're like put it all in this monstrosity and then use what's called. We use what's called a graph database and do vectoring, because you need that to make AI work and then have this cycle where we can start mining and the system just gets smarter and smarter, and I think we'll see that grow out of dealers who get a hold of their data first, and it's not just, as I said, the CRM, dms, website data. That's like table stakes today. You're going to have to go far beyond that to really leverage the power of LLMs and AI modeling. So I think we'll get there.
Speaker 2:I think in auto. I think auto has been stymied because of data movement. So what we've seen has been not great because data doesn't move very well, it doesn't move freely and we've seen it move freely in other industries and we've seen these amazing breakthroughs like Notion. You ever play with Notion. Notion's insane. Like if you had Notion in our business, oh my God. Like stuff would just be starting to disappear. Like CRM why would you buy that? Like it would be dumb. There would be no CRM and I don't think people understand that because they're in auto, we're not using those tools.
Speaker 1:Yeah.
Speaker 2:Right, because we live in a constrained environment. So we think the world is this auto and auto tech, but the real, the, there's a giant. It would almost be like you know, you think you're like the king of the neighborhood and then you go the next town and the next town's a giant city and you're like what the hell is this Like? You're just. You're just like, oh my God, I'm, I'm what I was the king of the neighborhood. Well, now I'm like, I'm nothing. Like what is going on.
Speaker 2:Like to me, it's like mind bending. Like, once you break free of the constraint thinking of of a typical dealership and look, dealers don't have a lot of time to do this. I'm going to say they don't have a lot of time to address AI and get ahead of it, but they also just don't have a lot of time because they're always running around, they're always plugging little tools and systems and they throw humans at things and they operate to me inefficient and they don't have a lot of times. And this is why I think things like a CDP and marketing one throat to choke and all these things have happened because the order is like how am I going to do all that? Like I'm just trying to sell cars. Todd, I need to save money. How do I combine tools, how do I get rid of my agency and save the money and do this? Like that's all they're thinking and they only think in 30-day cycles.
Speaker 2:Very few stores are literally projecting a year out and because they maybe can look at last year's doc for that month and there. But that's where I'm saying, like this is what AI is built for, dude, you can even add weather in, like when you start layering things and things, and AI is just like nom nom, nom, nom, nom. It's like Pac-Man Choo choo, choo, choo, choo choo. And then it starts kicking you back like, oh, this spring most likely is going to be wet, which is going to erode sales by three to 5%, because we see days that rained over the last five years, categorized.
Speaker 2:You saw a 5% reduction of sales on those days and we are predicting X days of rain this year. Think about that. That's where we're going. And oh, we see future constraints of inventory or all those things when they get mashed into these models. This is what's going to separate dealers. It's going to separate high performers from the also-rans and the also-rans will get gobbled hands down, so they'll just be gone, because that's the point, the one thing I always look at. Technology is indiscriminate.
Speaker 1:It's so true, it's true, it's so true, it's true. It's like data's the data, whoever has most wins.
Speaker 2:Look at on our planet right now, right, what do they control the most of? Is it the assets, the tools, their algos, google, facebook, amazon, apple? These are like data vacuum cleaners.
Speaker 1:So true.
Speaker 2:And think about it this way, like I always look at, which you're familiar with. You know telematics, right, all the data that the car is spitting out, right, and dealers are going to get screwed out of that data. That data was estimated to be worth $1.4 trillion. How much will dealers get of that? Nothing, oems are going to grab it, like I always looked at, like even Tesla. What is Tesla? On the surface it's a car company, but that's the surface. It's a giant data company. It's mapping everything. It's mapping your behavior. It knows where you go, when you went, how many times you went to Starbucks, how often do you go to school, do you go to the gym? Because it has location and behavior all intertwined and guess what you pay for the privilege of it. They should be paying us to drive a Tesla. Right, because it's crazy, the amount of data these things are giving Our cell phone, this in our pocket, right, your cell phone.
Speaker 1:I was just going to say this too Dude that too.
Speaker 2:And dealers have to start thinking like that, Like yeah, your data is that valuable Because, when we look at it at scale, the most valuable companies are all data companies.
Speaker 1:I think in the early days of talking about data and I'll circle back to this buzzword as we get ready to find a parking place for the core conversation wagon on this episode. But the big data thing, I do not think we have been serving the average dealer very well in the era of data and its importance, and so you may have some final thoughts, but I think this was yet another great conversation that dealers will. You know. Some of them are curious, some of them are opening their eyes. I think I would say make sure you're not one of the ones that hits the iceberg right Now. You're not just going to go down in your own data lake, you're going to go down in a data ocean.
Speaker 1:You gave some really good metaphors and I think, once again, I think dealers, when they can contextualize these concepts with things they've heard a lot, with their own circumstances, their own operations, I think it helps them get over the points of application within their own business, and I like that you take the time to make this type of content because I think that there are I know there are thousands of dealers that just want to do what they've always done I want to sell as many cars and service those cars.
Speaker 1:I want to make my customers really, really happy, and the speed of technology has been going so fast since the dawn of the internet really, but it's even before that that it makes it difficult for any business, any industry, to really keep up. Technology is moving extremely fast, faster than the average dealer is ever going to keep up with, and so you need to know where you can go for trusted information on concepts like this, and you're you're giving it out in spades, which is fantastic. I don't know if you have any final words for the episode, but I'll give you the floor.
Speaker 2:My, my final word is I always look at John Bannister. Right, ran the four minute mile before that. It was impossible. Right, he runs it within a year. Multiple people were able to run it.
Speaker 2:I think a lot of times we're still looking at ai is it's impossible, it's not going to do well that chat about? I play with chat gbt. It's not that good. You have no idea what's coming and and I think when it comes, it's going to come so fast and there's no catch up. And that's the most interesting thing about AI is, as you said, once you get going, if you enter the stream, you'll stay at the same difference as the person who entered the stream before you, because that's what it is. And AI learns from all your data and continues to improve and you continue to coach it like you bat it back and forth to fine-tune it, and this is why you know even uh, what's his name from open ai.
Speaker 2:Uh, altman said it's going to cost like a trillion dollars to truly program of an ad, a trillion, I think, or some. It was so crazy how much money that they he's like it's going to take and it's not now. It's not only the money it's going to take to train, it's the electrical resources necessary to do it. So, like Three Mile Island, microsoft is going to reopen part of it so they can literally use it to power their AI application. Because AI is such a energy suck and it'll just like dude, we'll all be like California with brownouts. Like because the AI is going to need to have all this processing power. And you know, as that final thought, like there is no better time to enter the stream than now and waiting isn't going to save you anything, it's not going to protect you from anything, it's only going to cause you headache and problems long-term.
Speaker 2:Because your AI is different than your competitor's AI. It's different than even a sister store's AI, and I try to localize that because the same with our partnership with Equifax. Like the data is so like narrowly scoped, that we can put two stores literally on the same property and the behavioral attributes of the customers who buy these stores is different. They fit in different, like what's called cohorts. It's insane and I go, oh, my gosh, and I was like data works the same way, meaning AI is under that same thing, that you wanted to train it on that granular of data that understands your customers who buy at that store, because you ultimately then want to attract more of those people to your dealership. That's how you sell more cars.
Speaker 1:I love it. There's to be an exclamation point at the end of that. To the audience listening and or watching, we always thank you for stopping by Core Conversations To learn a lot more about Core AI and all the things that Todd Smith is up to. Well, let's invite you to go to CoreAI. That's Q-O-R-E-A-Icom. Check out the website. There's a lot of information to consume there. Then also make sure if you are not following Todd Smith on LinkedIn especially.
Speaker 1:Todd absolutely pours out his heart as an entrepreneur, tells all the stories, a lot of weekend warrior stuff, and there's just not a lot of people in the industry that are as candid and transparent with really what's going on in his journey as he builds his company. So he's not only just helping dealers learn and get better and be prepared and get rid of this resistance to AI and understand why they would be saying yes or no to things, but he's telling you about the journey of Core AI as all of this is unfolding, and I personally I think it's fascinating and I hear from a lot of people in the industry that are loving that content. So make sure you follow him at LinkedIn, Go to coreaicom for more information and jump right back in here for another Core Conversation episode before you know it. If you're, oh, by the way, consuming this content in YouTube, like it, share it, subscribe to the channel and we'll be right back with another episode before you know it next month. Thanks for joining. Thanks, Todd.
Speaker 2:Thank you.